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IBM C1000-136 Exam Topics
Cloud Pak for Data Artechitecure 21%
Integration, Implementation, Deployment, and Scaling 10%
Analystics 17%
Build Data Science algorithms 14%
Machine learning Operations 16%
Data Governance 22%
Reference: https://www.ibm.com/training/certification/C0004601
What is the salary of IBM C1000-136 Exam
The Average salary of different countries for IBM C1000-136 Specialist:
United Kingdom - Pounds 76070 per year
India - INR 7249489 per year
United States - USD 93,000 per year
IBM C1000-136 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Governance | 22% | - Leverage the platform to understand data flow and usage - Capabilities of a data fabric topology - Use smart ingestion for auto cataloging - Map business opportunities into a data governance use case - Explain the use of Guardium in auditing and monitoring data - Explain the concepts of Knowledge Accelerators - Define the Governance structure - Understand how workflow is used in Cloud Pak for Data |
| Machine Learning Operations | 16% | - Monitor deployed models inside Cloud Pak for Data - Manage risk and regulatory compliance using OpenPages - Key considerations when selecting a platform for model deployment - Monitor machine learning models running on an external platform - Workflow of deploying and monitoring models |
| Build Data Science Algorithms | 14% | - Map business opportunities into a Data Science use case - Build and deploy ML/AI algorithms in Cloud Pak for Data - Differences between traditional programming and machine learning - Process and tools in Cloud Pak for Data to build, deploy, and monitor ML/AI algorithms - Collect, explore, and prepare data for ML/AI algorithms |
| Analytics | 17% | - Map business opportunities into an Analytics use case - Capabilities of business intelligence in Cloud Pak for Data - Capabilities of AI for financial operations in Cloud Pak for Data - Difference between Descriptive, Prescriptive, Predictive, Diagnostic, and Cognitive Analytics |
| Cloud Pak for Data Architecture | 21% | - Understand the underlying infrastructure and installation - Understand Cloud Pak for Data reliability options - Secure the solution and client data - Understand Cloud Pak for Data reference architecture - Understand sizing and deployment options |
| Integration, Implementation, Deployment, and Scaling | 10% | - Develop a strategy to monitor the Data and AI platform - Accelerate the solution using Industry Accelerators and External Data sets - Integrate Business Applications using Cloud Pak for Data - Develop process to take a Data and AI solution from inception to production |




